Expert approval certifies that test developers would use AI-generated items, not that the scores support valid interpretations. I extend argument-based validity with a generation inference and a five-layer evidence framework, apply it diagnostically to three NAEP–Wilbur evaluations, and propose design principles and a minimal reporting standard for the field.